AccScience Publishing / JCTR / Volume 5 / Issue 3 / DOI: 10.18053/jctres.05.202003.003
ORIGINAL ARTICLE

Investigation of quantitative susceptibility mapping in diagnosis of  tuberous sclerosis complex and assessment of associated brain injuries at  1.5 Tesla

Lei Zhang1,2 Hongqiang Xue3 Tao Chen3 Hongzhe Tian3 Xiaohu Wang3 Xiaocheng Wei4 Huawen Zhang4 Hui Ma1* Zhuanqin Ren3*
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1 Department of Radiology, Baoji Hi-Tech People’s Hospital, Baoji 721013, Shaanxi, P.R. China
2 Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an 710061, Shaanxi, P.R. China
3 Department of Radiology, Baoji Center Hospital, Baoji 721008, Shaanxi, P.R. China
4 GE Healthcare, Beijing, P.R. China
5 Department of Radiology, Nuclear Industry 215 Hospital of Shaanxi Province, Xianyang 712021, Shaanxi, P.R. China
Submitted: 30 August 2019 | Revised: 15 November 2019 | Accepted: 9 March 2020 | Published: 11 March 2020
© 2020 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Background and Aim: Tuberous sclerosis complex (TSC) is a rare disease with serious clinical consequences, such as mental deficiency and epilepsy. The pathological changes of TSC include demyelination and subependymal calcified nodules. Quantitative susceptibility mapping (QSM) is a newly developed imaging technique which is capable of quantitatively measuring the susceptibility induced by iron deposition, calcification and demyelination. The aim of this study was to investigate the use of QSM in detecting the subependymal nodules and assessing brain tissue injuries induced by cortical/subcortical tubers in TSC patients.
Methods: Twelve clinically confirmed TSC patients and fifteen gender and age matched healthy subjects underwent measurement with conventional magnetic resonance imaging (MRI) sequences, diffusion tensor imaging (DTI) and QSM. The TSC patients further underwent a computed tomography (CT) scan. Considering CT as the ground truth, the detection rates of subependymal nodules using conventional MR images and QSM was compared by the paired Chi square test, and the sensitivity, specificity were computed. The Bland-Altman test and independent t test was performed to compare the susceptibility of cortical/subcortical regions from QSM and fractional anisotropy (FA) values from DTI between the patient and control groups, pearson correlation was performed to examine the correlation between the susceptibility and FA values.
Results: QSM was better in detecting subependymal calcified nodules compared to conventional MR sequences (X2 = 40.18, p < 0.001), QSM achieved a significantly higher sensitivity of 98.3% and a lower specificity of 50%, which was compared with conventional MR sequences (46.7%, 75%, respectively). The susceptibility value of cortical/subcortical tubers in TSC patients was significantly higher than those in control group (t = 9.855, p < 0.001), while FA value was lower (t = -8.687, p < 0.001). Pearson correlation test revealed negative correlation between susceptibility and FA values in all participants (r = -0.65, p < 0.001).
Conclusions: QSM had similar ability in TSC compared to CT and DTI. QSM may provide valuable complementary information to conventional MRI imaging, and may simplity imaging of patients with TSC.
Relevance for patients: This study shows the feasibility of QSM to detect subependymal calcified nodules. It may provide quantitative information of white matter damage of tuberous sclerosis patients.

Keywords
magnetic resonance imaging
magnetic resonance imaging
tuberous sclerosis complex
Conflict of interest
The authors declare they have no competing interests.
References

[1] Caban C, Khan N, Hasbani DM, Crino PB. Genetics of Tuberous Sclerosis Complex: Implications for Clinical Practice. Appl Clin Genet 2016;10:1-8.

[2] O’Callaghan FJ, Shiell AW, Osborne JP, Martyn CN. Prevalence of Tuberous Sclerosis Estimated by Capture- recapture Analysis. Lancet 1998;351:1490.

[3] Sampson J, Scahill S, Stephenson J, Mann L, Connor JM. Genetic Aspects of Tuberous Sclerosis in the West of Scotland. J Med Genet 1989;26:28-31.

[4] RoachES. Applying the Lessons of Tuberous Sclerosis: The 2015 Hower Award Lecture. Pediatr Neurol 2016;63:6-22.

[5] Northrup H, Koenig MK, Pearson DA, Au KS. Tuberous Sclerosis Complex. In: Pagon RA, Adam MP, Ardinger HH, Wallace SE, Amemiya A, Bean LJ, et al, editors. GeneReviews® [Internet]. Seattle (WA): University of Washington, Seattle; 1999.

[6] Northrup H, Kruger D, International Tuberous Sclerosis Complex Consensus Group. Tuberous Sclerosis Complex Diagnostic Criteria Update: Recommendations of the 2012 International Tuberous Sclerosis Complex Consensus Conference. Pediatr Neurol 2013;49:243-54.

[7] von Ranke FM, Faria IM, Zanetti G, Hochhegger B, Souza AS Jr., Marchiori E. Imaging of Tuberous Sclerosis Complex: A Pictorial Review. Radiol Bras 2017;50:48-54.

[8] CuratoloP, JozwiakS, Nabbout R,TSC Consensus Meeting for SEGA and Epilepsy Management. Management of Epilepsy Associated with Tuberous Sclerosis Complex (TSC): Clinical Recommendations. Eur J Paediatr Neurol 2012;16:582-6.

[9] Rafal RB, Ndzengue A, Jaffe EA. Tuberous Sclerosis: Computed Tomography Diagnosis. J Emerg Med 2013;44:e259-61.

[10] Roth J, Roach ES, Bartels U, Jozwiak S, Koenig MK, Weiner HL, et al. Subependymal Giant Cell Astrocytoma: Diagnosis, Screening, and Treatment. Recommendations from the International Tuberous Sclerosis Complex Consensus Conference. Pediatr Neurol 2012;49:439-44.

[11] Vezina G, BarkovichAJ. Tuberous Sclerosis Complex. In: BarkovichAJ,Raybaud C, editors. Pediatric Neuroimaging. Philadelphia, PA: Lippincott Williams & Wilkins; 2011. p. 593-605.

[12] Umeoka S, Koyama T, Miki Y, Akai M, Tsutsui K, Togashi K. Pictorial Review of Tuberous Sclerosis in Various Organs. Radiographics 2008;28:e32.

[13] Liang S, Zhang J, Yang Z, Zhang S, Cui Z, Cui J, et al. Long-term Outcomes of Epilepsy Surgery in Tuberous Sclerosis Complex. J Neurol 2017;264:1146-54.

[14] Gama HP, da Rocha AJ, Braga FT, da Silva CJ, Maia AC Jr., de Campos Meirelles RG, et al. Comparative Analysis of MR Sequences to Detect Structural Brain Lesions in Tuberous Sclerosis. Pediatr Radiol 2006;36:119-25.

[15] Pfefferbaum A, Adalsteinsson E, Rohlfing T, Sullivan EV. Diffusion Tensor Imaging of Deep Gray Matter Brain Structures: Effects of Age and Iron Concentration. Neurobiol Aging 2010;31:482-93.

[16] Zikou AK, XydisVG, Astrakas LG, NakouI, TzarouchiLC, TzoufiM, et al. Diffusion Tensor Imaging in Children with Tuberous Sclerosis Complex: Tract-based Spatial Statistics Assessment of Brain Microstructural Changes. Pediatr Radiol 2016;46:1158-64.

[17] Dogan MS, GumusK, KocG,DoganayS, Per H, GorkemSB, et al. Brain Diffusion Tensor Imaging in Children with Tuberous Sclerosis. Diagn Interv Imaging 2016;97:171-6.

[18] Yogi A, HirataY, Karavaeva E, Harris RJ, Wu JY, Yudovin SL, et al. DTI of Tuber and Perituberal Tissue Can Predict Epileptogenicity in Tuberous Sclerosis Complex. Neurology 2015;85:2011-5.

[19] An H, Zeng X, Niu T, Li G, Yang J, Zheng L, et al. Quantifying Iron Deposition Within the Substantia Nigra of Parkinson’s Disease by Quantitative Susceptibility Mapping. J Neurol Sci 2018;386:46-52.

[20] de Rochefort L, Liu T, Kressler B, Liu J, Spincemaille P, Lebon V, et al. Quantitative Susceptibility Map Reconstruction from MR Phase Data Using Bayesian Regularization:   Validation   and Application   to   Brain Imaging. Magn Reson Med 2010;63:194-206.

[21]    Schweser  F,  Deistung  A,  Reichenbach  JR.  Foundations of MRI Phase  Imaging  and  Processing  for  Quantitative Susceptibility Mapping (QSM). Z Med Phys 2016;26:6-34.

[22]    Liu  C, Wei H,  Gong NJ, Cronin M, Dibb R, Decker K. Quantitative Susceptibility Mapping: Contrast Mechanisms and Clinical Applications. Tomography 2015;1:3-17.

[23]   Haacke  EM,  Liu  S,  Buch  S,  Zheng  W,  Wu  D, Ye Y. Quantitative Susceptibility Mapping: Current Status and Future Directions. Magn Reson Imaging 2015;33:1-25.

[24]    He  N,  Ling  H,  Ding  B,  Huang  J,  Zhang  Y,  Zhang  Z, et al. Region specific Disturbed Iron Distribution in Early Idiopathic  Parkinson’s  Disease  Measured by  Quantitative Susceptibility Mapping. Hum Brain Mapp 2015;36:4407-20.

[25]    Randle   SC.   Tuberous   Sclerosis   Complex:  A   Review. PediatrAnn 2017;46:e166-71.

[26]    Wu  Z,   Mittal  S,  Kish  K,  Yu  Y,   Hu  J,  Haacke  EM. Identification     of    Calcification     with     MRI     Using Susceptibility-weighted Imaging: A Case Study. J Magn Reson Imaging 2009;29:177-82.

[27]    Deistung    A,    Schweser   F,    Wiestler    B,   Abello    M, Roethke  M,  Sahm  F,  et  al.  Quantitative  Susceptibility Mapping Differentiates Between Blood Depositions and Calcifications in Patients with Glioblastoma. PLoS One 2013;8:e57924.

[28]    Wang Y,  Spincemaille P,  Liu Z, Dimov A, Deh K, Li J, et al. Clinical Quantitative Susceptibility Mapping (QSM): Biometal Imaging and Its Emerging Roles in Patient Care. J Magn Reson Imaging 2017;46:951-71.

[29]   Liu T, Khalidov I, de Rochefort L, Spincemaille P, Liu J, Tsiouris AJ, et al. A Novel Background Field Removal Method  for  MRI  Using  Projection  onto  Dipole  Fields (PDF). NMR Biomed 2011;24:1129-36.

[30]    Chen W,  Zhu W,  Kovanlikaya I, Kovanlikaya A, Liu T, Wang S, et al. Intracranial Calcifications and Hemorrhages: Characterization with Quantitative Susceptibility Mapping. Radiology 2014;270:496-505.

[31]    AuKS, Williams AT, RoachES, BatchelorL, Sparagana SP, Delgado MR, et al. Genotype/Phenotype Correlation in 325 Individuals Referred for a Diagnosis of Tuberous Sclerosis Complex in the United States. Genet Med 2007;9:88-100.

[32]    Curatolo   P,  Verdecchia  M,  Bombardieri  R.  Tuberous Sclerosis Complex: A Review of Neurological Aspects. Eur J Paediatr Neurol 2002;6:15-23.

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Journal of Clinical and Translational Research, Electronic ISSN: 2424-810X Print ISSN: 2382-6533, Published by AccScience Publishing